Literature DB >> 26250979

Radiogenomics: what it is and why it is important.

Maciej A Mazurowski1.   

Abstract

In recent years, a new direction in cancer research has emerged that focuses on the relationship between imaging phenotypes and genomics. This direction is referred to as radiogenomics or imaging genomics. The question that subsequently arises is: What is the practical significance of elucidating this relationship in improving cancer patient outcomes. In this article, I address this question. Although I discuss some limitations of the radiogenomic approach, and describe scenarios in which radiogenomic analysis might not be the best choice, I also argue that radiogenomics will play a significant practical role in cancer research. Specifically, I argue that the significance of radiogenomics is largely related to practical limitations of currently available data that often lack complete characterization of the patients and poor integration of individual datasets. Radiogenomics offers a practical way to leverage limited and incomplete data to generate knowledge that might lead to improved decision making, and as a result, improved patient outcomes.
Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2015        PMID: 26250979     DOI: 10.1016/j.jacr.2015.04.019

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  72 in total

1.  Radiomics nomogram of contrast-enhanced spectral mammography for prediction of axillary lymph node metastasis in breast cancer: a multicenter study.

Authors:  Ning Mao; Ping Yin; Qin Li; Qinglin Wang; Meijie Liu; Heng Ma; Jianjun Dong; Kaili Che; Zhongyi Wang; Shaofeng Duan; Xuexi Zhang; Nan Hong; Haizhu Xie
Journal:  Eur Radiol       Date:  2020-06-30       Impact factor: 5.315

2.  A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

Authors:  Ashirbani Saha; Michael R Harowicz; Weiyao Wang; Maciej A Mazurowski
Journal:  J Cancer Res Clin Oncol       Date:  2018-02-09       Impact factor: 4.553

3.  Imaging Informatics: 25 Years of Progress.

Authors:  J P Agrawal; B J Erickson; C E Kahn
Journal:  Yearb Med Inform       Date:  2016-06-30

Review 4.  The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part I).

Authors:  Tanvi Vaidya; Archi Agrawal; Shivani Mahajan; Meenakshi H Thakur; Abhishek Mahajan
Journal:  Mol Diagn Ther       Date:  2019-02       Impact factor: 4.074

5.  Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.

Authors:  Andreas Mang; Spyridon Bakas; Shashank Subramanian; Christos Davatzikos; George Biros
Journal:  Annu Rev Biomed Eng       Date:  2020-06-04       Impact factor: 9.590

6.  Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

Authors:  Chiharu Kai; Yoshikazu Uchiyama; Junji Shiraishi; Hiroshi Fujita; Kunio Doi
Journal:  Radiol Phys Technol       Date:  2018-05-10

7.  Correlations between metabolic texture features, genetic heterogeneity, and mutation burden in patients with lung cancer.

Authors:  Seung Hwan Moon; Jinho Kim; Je-Gun Joung; Hongui Cha; Woong-Yang Park; Jin Seok Ahn; Myung-Ju Ahn; Keunchil Park; Joon Young Choi; Kyung-Han Lee; Byung-Tae Kim; Se-Hoon Lee
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-08-25       Impact factor: 9.236

8.  Radiomic features predict Ki-67 expression level and survival in lower grade gliomas.

Authors:  Yiming Li; Zenghui Qian; Kaibin Xu; Kai Wang; Xing Fan; Shaowu Li; Xing Liu; Yinyan Wang; Tao Jiang
Journal:  J Neurooncol       Date:  2017-09-12       Impact factor: 4.130

9.  Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?

Authors:  Michael R Harowicz; Ashirbani Saha; Lars J Grimm; P Kelly Marcom; Jeffrey R Marks; E Shelley Hwang; Maciej A Mazurowski
Journal:  J Magn Reson Imaging       Date:  2017-02-09       Impact factor: 4.813

Review 10.  Background, applications and challenges of radiogenomics in genitourinary tumor.

Authors:  Longfei Liu; Xiaoping Yi; Can Lu; Yingxian Pang; Xiongbing Zu; Minfeng Chen; Xiao Guan
Journal:  Am J Cancer Res       Date:  2021-05-15       Impact factor: 6.166

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